from typing import TYPE_CHECKING

from ...utils import (
    OptionalDependencyNotAvailable,
    _LazyModule,
    is_flax_available,
    is_tf_available,
    is_tokenizers_available,
    is_torch_available,
)


A						=			{
    'configuration_blenderbot': [
        'BLENDERBOT_PRETRAINED_CONFIG_ARCHIVE_MAP',
        'BlenderbotConfig',
        'BlenderbotOnnxConfig',
    ],
    'tokenization_blenderbot': ['BlenderbotTokenizer'],
}

try:
				if not is_tokenizers_available():
								raise OptionalDependencyNotAvailable()
except OptionalDependencyNotAvailable:
				pass
else:
				A						=			['BlenderbotTokenizerFast']

try:
				if not is_torch_available():
								raise OptionalDependencyNotAvailable()
except OptionalDependencyNotAvailable:
				pass
else:
				A						=			[
				    'BLENDERBOT_PRETRAINED_MODEL_ARCHIVE_LIST',
				    'BlenderbotForCausalLM',
				    'BlenderbotForConditionalGeneration',
				    'BlenderbotModel',
				    'BlenderbotPreTrainedModel',
				]


try:
				if not is_tf_available():
								raise OptionalDependencyNotAvailable()
except OptionalDependencyNotAvailable:
				pass
else:
				A						=			[
				    'TFBlenderbotForConditionalGeneration',
				    'TFBlenderbotModel',
				    'TFBlenderbotPreTrainedModel',
				]


try:
				if not is_flax_available():
								raise OptionalDependencyNotAvailable()
except OptionalDependencyNotAvailable:
				pass
else:
				A						=			[
				    'FlaxBlenderbotForConditionalGeneration',
				    'FlaxBlenderbotModel',
				    'FlaxBlenderbotPreTrainedModel',
				]


if TYPE_CHECKING:
				from .configuration_blenderbot import (
				    BLENDERBOT_PRETRAINED_CONFIG_ARCHIVE_MAP,
				    BlenderbotConfig,
				    BlenderbotOnnxConfig,
				)
				from .tokenization_blenderbot import BlenderbotTokenizer

				try:
								if not is_tokenizers_available():
												raise OptionalDependencyNotAvailable()
				except OptionalDependencyNotAvailable:
								pass
				else:
								from .tokenization_blenderbot_fast import BlenderbotTokenizerFast

				try:
								if not is_torch_available():
												raise OptionalDependencyNotAvailable()
				except OptionalDependencyNotAvailable:
								pass
				else:
								from .modeling_blenderbot import (
								    BLENDERBOT_PRETRAINED_MODEL_ARCHIVE_LIST,
								    BlenderbotForCausalLM,
								    BlenderbotForConditionalGeneration,
								    BlenderbotModel,
								    BlenderbotPreTrainedModel,
								)

				try:
								if not is_tf_available():
												raise OptionalDependencyNotAvailable()
				except OptionalDependencyNotAvailable:
								pass
				else:
								from .modeling_tf_blenderbot import (
								    TFBlenderbotForConditionalGeneration,
								    TFBlenderbotModel,
								    TFBlenderbotPreTrainedModel,
								)

				try:
								if not is_flax_available():
												raise OptionalDependencyNotAvailable()
				except OptionalDependencyNotAvailable:
								pass
				else:
								from .modeling_flax_blenderbot import (
								    FlaxBlenderbotForConditionalGeneration,
								    FlaxBlenderbotModel,
								    FlaxBlenderbotPreTrainedModel,
								)

else:
				import sys

				A						=			_LazyModule(__name__, globals()['__file__'], _import_structure, module_spec=__spec__)
def 	lowerCamelCase					(	UpperCamelCase     :				int			,       UpperCamelCase     :				int							)   ->    str:
		if number < 0 or shift_amount < 0:
				raise ValueError('both inputs must be positive integers'							)

		_lowerCamelCase				   =  str(bin(UpperCamelCase							)							)
		binary_number += "0" * shift_amount
		return binary_number


def 	lowerCamelCase					(	UpperCamelCase     :				int			,       UpperCamelCase     :				int							)   ->    str:
		if number < 0 or shift_amount < 0:
				raise ValueError('both inputs must be positive integers'							)

		_lowerCamelCase				   =  str(bin(UpperCamelCase							)							)[2:]
		if shift_amount >= len(UpperCamelCase							):
				return "0b0"
		_lowerCamelCase				   =  binary_number[: len(UpperCamelCase							) - shift_amount]
		return "0b" + shifted_binary_number


def 	lowerCamelCase					(	UpperCamelCase     :				int			,       UpperCamelCase     :				int							)   ->    str:
		if number >= 0:  # Get binary representation of positive number
				_lowerCamelCase				   =  '0' + str(bin(UpperCamelCase							)							).strip('-'							)[2:]
		else:  # Get binary (2's complement) representation of negative number
				_lowerCamelCase				   =  len(bin(UpperCamelCase							)[3:]							)  # Find 2's complement of number
				_lowerCamelCase				   =  bin(abs(UpperCamelCase							) - (1 << binary_number_length)							)[3:]
				_lowerCamelCase				   =  (
				    '1' + '0' * (binary_number_length - len(UpperCamelCase							)) + binary_number
				)

		if shift_amount >= len(UpperCamelCase							):
				return "0b" + binary_number[0] * len(UpperCamelCase							)
		return (
		    "0b"
		    + binary_number[0] * shift_amount
		    + binary_number[: len(UpperCamelCase							) - shift_amount]
		)


if __name__ == "__main__":
				import doctest

				doctest.testmod()